Quick Summary: Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs Cheng Wang, senior vice president of engineering at Flex Logix, talks with Semiconductor Engineering about the

Dwm A Decomposable Winograd Method For Convolution Acceleration -

Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs Cheng Wang, senior vice president of engineering at Flex Logix, talks with Semiconductor Engineering about the This is a 5-minutes introduction to my paper published in EuroSyS 2020 conference related to the

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  • Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs
  • Cheng Wang, senior vice president of engineering at Flex Logix, talks with Semiconductor Engineering about the
  • This is a 5-minutes introduction to my paper published in EuroSyS 2020 conference related to the
  • This is my presentation for my paper published in EuroSyS 2020 conference related to the
  • Official presentation of the CVPR 2022 poster paper "Channel Balancing for Accurate Quantization of

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DWM: A Decomposable Winograd Method for Convolution Acceleration
[Long version] Accelerating Winograd convolutions using symbolic computation and meta-programming
The Winograd Transformation
David Gregg - "Improving the Accuracy and Speed of Winograd Convolution for Deep Neural Networks"
Fast Convolution based on Winograd Minimum Filtering: Introduction and Development
tinyML Summit 2021 tiny Talks: Low-precision Winograd Convolution over Residue Number System
Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs
[Short version] Accelerating Winograd convolutions using symbolic computation and meta-programming
CVPR 2022: Channel Balancing for Accurate Quantization of Winograd Convolutions
Session 7B: Optimizing Winograd-Based Convolution with Tensor Cores
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DWM: A Decomposable Winograd Method for Convolution Acceleration

DWM: A Decomposable Winograd Method for Convolution Acceleration

Read more details and related context about DWM: A Decomposable Winograd Method for Convolution Acceleration.

[Long version] Accelerating Winograd convolutions using symbolic computation and meta-programming

[Long version] Accelerating Winograd convolutions using symbolic computation and meta-programming

This is my presentation for my paper published in EuroSyS 2020 conference related to the

The Winograd Transformation

The Winograd Transformation

Cheng Wang, senior vice president of engineering at Flex Logix, talks with Semiconductor Engineering about the

David Gregg - "Improving the Accuracy and Speed of Winograd Convolution for Deep Neural Networks"

David Gregg - "Improving the Accuracy and Speed of Winograd Convolution for Deep Neural Networks"

David Gregg Professor in Computer Science, Trinity College Dublin

Fast Convolution based on Winograd Minimum Filtering: Introduction and Development

Fast Convolution based on Winograd Minimum Filtering: Introduction and Development

Read more details and related context about Fast Convolution based on Winograd Minimum Filtering: Introduction and Development.

tinyML Summit 2021 tiny Talks: Low-precision Winograd Convolution over Residue Number System

tinyML Summit 2021 tiny Talks: Low-precision Winograd Convolution over Residue Number System

tinyML Summit 2021 tinyTalks Algorithms and Tools "Low-precision

Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs

Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs

Session 7B: LoWino: Towards Efficient Low Precision Winograd Convolutions on Modern CPUs

[Short version] Accelerating Winograd convolutions using symbolic computation and meta-programming

[Short version] Accelerating Winograd convolutions using symbolic computation and meta-programming

This is a 5-minutes introduction to my paper published in EuroSyS 2020 conference related to the

CVPR 2022: Channel Balancing for Accurate Quantization of Winograd Convolutions

CVPR 2022: Channel Balancing for Accurate Quantization of Winograd Convolutions

Official presentation of the CVPR 2022 poster paper "Channel Balancing for Accurate Quantization of

Session 7B: Optimizing Winograd-Based Convolution with Tensor Cores

Session 7B: Optimizing Winograd-Based Convolution with Tensor Cores

Session 7B: Optimizing Winograd-Based Convolution with Tensor Cores